A limited memory algorithm for bound constrained optimization
SIAM Journal on Scientific Computing
A maximum entropy approach to natural language processing
Computational Linguistics
Prosody-based automatic segmentation of speech into sentences and topics
Speech Communication - Special issue on accessing information in spoken audio
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
Edit detection and parsing for transcribed speech
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
Learning the Threshold in Hierarchical Agglomerative Clustering
ICMLA '06 Proceedings of the 5th International Conference on Machine Learning and Applications
A TAG-based noisy channel model of speech repairs
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Parsing conversational speech using enhanced segmentation
HLT-NAACL-Short '04 Proceedings of HLT-NAACL 2004: Short Papers
A lexically-driven algorithm for disfluency detection
HLT-NAACL-Short '04 Proceedings of HLT-NAACL 2004: Short Papers
Probabilistic latent semantic analysis
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Multistage speaker diarization of broadcast news
IEEE Transactions on Audio, Speech, and Language Processing
Enriching speech recognition with automatic detection of sentence boundaries and disfluencies
IEEE Transactions on Audio, Speech, and Language Processing
An overview of automatic speaker diarization systems
IEEE Transactions on Audio, Speech, and Language Processing
Recognizing disfluencies in conversational speech
IEEE Transactions on Audio, Speech, and Language Processing
Edit disfluency detection and correction using a cleanup language model and an alignment model
IEEE Transactions on Audio, Speech, and Language Processing
ACM Transactions on Asian Language Information Processing (TALIP)
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Detection of edit disfluencies is key to transcribing spontaneous utterances. In this paper, we present improved features and models to detect edit disfluencies and enhance transcription of spontaneous Mandarin speech using hypothesized disfluency interruption points (IPs) and edit word detection. A comprehensive set of prosodic features that takes into account the special characteristics of edit disfluencies in Mandarin is developed, and an improved model combining decision trees and maximum entropy is proposed to detect IPs. This model is further adapted to desired prosodic conditions by latent prosodic modeling, a probabilistic framework for analyzing speech prosody in terms of a set of latent prosodic states. These techniques contribute to higher recognition accuracy (by rescoring with the hypothesized IPs) and better edit word detection (using conditional random fields defined on Chinese characters) in the final transcription, as verified by experiments on a spontaneous Mandarin speech corpus.